• Asian Pacific Journal of Cancer Prevention
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• v.15 no.22
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• pp.9643-9647
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• 2014

Background: Several studies have been performed to investigate the association of the HER2 Ile655Val polymorphism and breast cancer risk. However, the results were inconsistent. To understand the precise relationship, a meta-analysis was here conducted. Materials and Methods: A search of PubMed conducted to investigate links between the HER2 Ile655Val polymorphism and breast cancer, identified a total of 32 studies, of which 29, including 14,926 cases and 15,768 controls, with odds ratios (ORs) with 95% confidence intervals were used to assess any association. Results: In the overall analysis, the HER2 Ile655Val polymorphism was associated with breast cancer in an additive genetic model (OR=1.136, 95% CI 1.043-1.239, p=0.004) and in a dominant genetic (OR=1.118, 95% CI 1.020-1.227, p=0.018), while no association was found in a recessive genetic model. On subgroup analysis, an association with breast cancer was noted in the additive genetic model (OR=1.111, 95% CI: 1.004-1.230, p=0.042) for the Caucasian subgroup. No significant associations were observed in Asians and Africans in any of the genetic models. Conclusions: In summary, our meta-analysis findings suggest that the HER2 Ile655Val polymorphism is marginally associated with breast cancer susceptibility in worldwide populations with additive and dominant models, but not a recessive model.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5571-5575
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• 2014

Background: The ability to predict the survival time of breast cancer patients is important because of the potential high morbidity and mortality associated with the disease. To develop a predictive inference for determining the survival of breast cancer patients, we applied a novel Bayesian method. In this paper, we propose the development of a databased statistical probability model and application of the Bayesian method to predict future survival times for White Hispanic female breast cancer patients, diagnosed in the US during 1973-2009. Materials and Methods: A stratified random sample of White Hispanic female patient survival data was selected from the Surveillance Epidemiology and End Results (SEER) database to derive statistical probability models. Four were considered to identify the best-fit model. We used three standard model-building criteria, which included Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) to measure the goodness of fit. Furthermore, the Bayesian method was used to derive future survival inferences for survival times. Results: The highest number of White Hispanic female breast cancer patients in this sample was from New Mexico and the lowest from Hawaii. The mean (SD) age at diagnosis (years) was 58.2 (14.2). The mean (SD) of survival time (months) for White Hispanic females was 72.7 (32.2). We found that the exponentiated Weibull model best fit the survival times compared to other widely known statistical probability models. The predictive inference for future survival times is presented using the Bayesian method. Conclusions: The findings are significant for treatment planning and health-care cost allocation. They should also contribute to further research on breast cancer survival issues.

• Toxicological Research
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• v.29 no.4
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• pp.229-234
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• 2013

Phytoestrogens exist in edible compounds commonly found in fruits or plants. For long times, phytoestrogens have been used for therapeutic treatments against human diseases, and they can be promising ingredients for future pharmacological industries. Kaempferol is a yellow compound found in grapes, broccoli and yellow fruits, which is one of flavonoid as phytoestrogens. Kaempferol has been suggested to have an antioxidant and anti-inflammatory effect. In past decades, many studies have been performed to examine anti-toxicological role(s) of kaempferol against human cancers. It has been shown that kaempferol may be involved in the regulations of cell cycle, metastasis, angiogenesis and apoptosis in various cancer cell types. Among them, there have been a few of the studies to examine a relationship between kaempferol and apoptosis. Thus, in this review, we highlight the effect(s) of kaempferol on the regulation of apoptosis in diverse cancer cell models. This could be a forecast in regard to use of kaempferol as promising treatment against human diseases.

• Journal of Pharmacopuncture
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• v.20 no.4
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• pp.265-273
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• 2017

Objective: Orthosiphon pallidus (O. pallidus), which belongs to the Lamiaceae family, is a popular garden plant that is widely used for the treatment of various diseases, such as urinary lithiasis, fever, hepatitis, cancer and jaundice. The objective of the present work was to investigate the antioxidant free-radical scavenging and the anticancer activities of O. pallidus against human breast-cancer cell lines. Methods: The antioxidant activity of Orthosiphon pallidus aqueous extract (OPAE) was investigated using different models, such as the 1,1-diphenyl-2-picrylhydrazyl (DPPH) and the 2, 2'-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) models, as were the $Fe^+$ chelation, the hydroxyl radical and superoxide radical scavenging, and total reducing power activities. The anticancer activities of the extract were determined by using the 3-(4, 5- dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide (MTT) and the sulforhodamine (SRB) assays on the MCF-7 and the MDA-MB-231 cancer cell lines. Results: The aqueous Orthosiphon pallidus extract showed potent activity in in-vitro models. It significantly inhibited the scavenging of hydroxyl and superoxide radicals, but induced a remarkable $Fe^+$ chelation activity. For both cell lines, the percent cytotoxicity was found to increase steadily with increasing OPAE concentration up to $240{\mu}g/mL$. Conclusion: These results suggest that Orthosiphon pallidus has excellent antioxidant, antimicrobial, and anticancer activities against human breast-cancer cell lines.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1193-1196
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• 2016

Background: Colorectal cancer (CRC) is the commonest malignancy in the lower gastrointestinal tract in both men and women. It is the third leading cause of cancer-dependent death in the world. In Iran the incidence of colorectal cancer has increased during the last 25 years. Materials and Methods: In this article we analyzed the survival of 447 colorectal patients of Taleghani hospital in Tehran using parametric competing-risks models. The cancers of these patients were diagnosed during 1985 - 2012 and followed up to 2013. The purpose was to assess the association between survival of patients with colorectal cancer in the presence of competing-risks and prognostic factors using parametric models. The analysis was carried out using R software version 3.0.2. Results: The prognostic variables included in the model were age at diagnosis, tumour site, body mass index and sex. The effect of age at diagnosis and body mass index on survival time was statistically significant. The median survival for Iranian patients with colorectal cancer is about 20 years. Conclusions: Survival function based on Weibull model compared with Kaplan-Meier survival function is smooth. Iranian data suggest a younger age distribution compared to Western reports for CRC.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7057-7063
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• 2013

The discovery of the immunodeficient mice has provided a tool for establishing animal models as hosts for in vivo analysis of AML. Various model systems have been established in the last few decades, and it is essential that murine AML models are developed to exploit more specific, targeted therapeutics. In this review, we concentrate on the models of AML and discuss the development of immunodeficiency models for understanding of leukemogenesis, describe those now available and their values and document the methods used for establishing and identifying AML mice models, as well as factors influencing engraftment of human AML in immunodeficient mice. Thus, the function of this article is to provide clinicians and experimentalists with a chronological, comprehensive appraisal of all AML model systems.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.9
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• pp.4049-4054
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• 2014

Background: Race and ethnicity are significant factors in predicting survival time of breast cancer patients. In this study, we applied advanced statistical methods to predict the survival of White non-Hispanic female breast cancer patients, who were diagnosed between the years 1973 and 2009 in the United States (U.S.). Materials and Methods: Demographic data from the Surveillance Epidemiology and End Results (SEER) database were used for the purpose of this study. Nine states were randomly selected from 12 U.S. cancer registries. A stratified random sampling method was used to select 2,000 female breast cancer patients from these nine states. We compared four types of advanced statistical probability models to identify the best-fit model for the White non-Hispanic female breast cancer survival data. Three model building criterion were used to measure and compare goodness of fit of the models. These include Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC). In addition, we used a novel Bayesian method and the Markov Chain Monte Carlo technique to determine the posterior density function of the parameters. After evaluating the model parameters, we selected the model having the lowest DIC value. Using this Bayesian method, we derived the predictive survival density for future survival time and its related inferences. Results: The analytical sample of White non-Hispanic women included 2,000 breast cancer cases from the SEER database (1973-2009). The majority of cases were married (55.2%), the mean age of diagnosis was 63.61 years (SD = 14.24) and the mean survival time was 84 months (SD = 35.01). After comparing the four statistical models, results suggested that the exponentiated Weibull model (DIC= 19818.220) was a better fit for White non-Hispanic females' breast cancer survival data. This model predicted the survival times (in months) for White non-Hispanic women after implementation of precise estimates of the model parameters. Conclusions: By using modern model building criteria, we determined that the data best fit the exponentiated Weibull model. We incorporated precise estimates of the parameter into the predictive model and evaluated the survival inference for the White non-Hispanic female population. This method of analysis will assist researchers in making scientific and clinical conclusions when assessing survival time of breast cancer patients.

• Proceedings of the Korean Society of Toxicology Conference
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• 1998.10a
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• pp.58-59
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• 1998

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.3
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• pp.1057-1062
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• 2015

Background: Since the survival rate of breast cancer patients has improved, harmful effects of new treatment modalities on fertility of the young breast cancer patients has become a focus of attention. This study aimed to systematically review and critically appraise all available guidelines for fertility preservation in young breast cancer patients. Materials and Methods: Major citation databases were searched for treatment guidelines. Experts from relevant disciplines appraised the available guidelines. The AGREE II Instrument that includes 23 criteria in seven domains (scope and purpose of the guidelines, stakeholder involvement, rigor of development, clarity, applicability, editorial independence, and overall quality) was used to apprise and score the guidelines. Results: The search strategy retrieved 2,606 citations; 72 were considered for full-text screening and seven guidelines were included in the study. There was variability in the scores assigned to different domains among the guidelines. ASCO (2013), with an overall score of 68.0%, had the highest score, and St Gallen, with an overall score of 24.7%, had the lowest scores among the guidelines. Conclusions: With the promising survival rate among breast cancer patients, more attention should be given to include specific fertility preservation recommendations for young breast cancer patients.

• BMB Reports
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• v.56 no.1
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• pp.24-31
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• 2023

Urological cancers such as kidney, bladder, prostate, and testicular cancers are the most common types of cancers worldwide with high mortality and morbidity. To date, traditional cell lines and animal models have been broadly used to study pre-clinical applications and underlying molecular mechanisms of urological cancers. However, they cannot reflect biological phenotypes of real tissues and clinical diversities of urological cancers in vitro system. In vitro models cannot be utilized to reflect the tumor microenvironment or heterogeneity. Cancer organoids in three-dimensional culture have emerged as a promising platform for simulating tumor microenvironment and revealing heterogeneity. In this review, we summarize recent advances in prostate and kidney cancer organoids regarding culture conditions, advantages, and applications of these cancer organoids.